{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5d8459ca-6c88-4a16-8c94-780a14319667",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>BiGRU 多变量时间序列预测(PyTorch版)</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e650f06c-9d7a-4702-988b-e73ea14a6efa",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>在当今数据驱动的时代，时间序列预测已成为众多领域不可或缺的工具，无论是金融市场的波动预测、气象数据的趋势分析，还是交通流量的监控预测，都离不开对时间序列数据的深入研究。在这些场景中，往往需要考虑多个变量之间的相互影响，因此，多变量时间序列预测成为了研究的热点和难点。\n",
    "\n",
    "<font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>本文旨在介绍基于PyTorch框架的BiGRU多变量时间序列预测算法的实现。双向门控循环单元（BiGRU）作为BiRNN的一种变体，结合了GRU和BiRNN的优点，不仅具有更强的学习能力，而且能够同时考虑到历史和未来的信息。在多变量时间序列预测中，BiGRU可以通过其双向结构和门控机制，有效地捕捉多个变量之间的相互影响和时序关系，从而实现更准确的预测。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e70d78c1-d153-4b0f-83cf-5110257f7442",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.model_selection import TimeSeriesSplit\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.utils.data import DataLoader, TensorDataset\n",
    "from torchinfo import summary\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64a97d83-6af5-46d2-9856-65382cf76dea",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Data preprocessing</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f16ce31e-f5fa-4538-baef-c2742f18303e",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= 'orange'>**pandas.to_datetime**</font> <font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>function converts a scalar, array-like, Series or DataFrame/dict-like to a pandas datetime object.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c20ca98f-3b2f-45ba-8931-8b6c4fc8886e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'numpy.float64'> <class 'str'>\n",
      "<class 'numpy.float64'> <class 'pandas._libs.tslibs.timestamps.Timestamp'>\n",
      "(755, 6)\n"
     ]
    }
   ],
   "source": [
    "AAPL = pd.read_csv('AAPL.csv')\n",
    "print(type(AAPL['Close'].iloc[0]),type(AAPL['Date'].iloc[0]))\n",
    "# Let's convert the data type of timestamp column to datatime format\n",
    "AAPL['Date'] = pd.to_datetime(AAPL['Date'])\n",
    "print(type(AAPL['Close'].iloc[0]),type(AAPL['Date'].iloc[0]))\n",
    "\n",
    "# Selecting subset\n",
    "cond_1 = AAPL['Date'] >= '2021-04-23 00:00:00'\n",
    "cond_2 = AAPL['Date'] <= '2024-04-23 00:00:00'\n",
    "AAPL = AAPL[cond_1 & cond_2].set_index('Date')\n",
    "print(AAPL.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a1ee0b3-5cbe-465e-ba42-19b7556d0a6a",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Data visualisation</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa1e9596-8342-461b-8399-d85925d74f3e",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>The closing price is the last price at which the stock is traded during the regular trading day. A stock’s closing price is the standard benchmark used by investors to track its performance over time.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c4799310-296d-47cd-acea-4c488a65bdb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.style.available\n",
    "plt.style.use('_mpl-gallery')\n",
    "plt.figure(figsize=(18,6))\n",
    "plt.title('Close Price History')\n",
    "plt.plot(AAPL['Close'],label='AAPL')\n",
    "plt.ylabel('Close Price USD ($)', fontsize=18)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31ba7f06-84a7-4a37-9ddf-87f71f6b38bb",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Feature Engineering</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4351f13a-876e-4432-8a56-1caba0e6b6c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 设置时间回溯窗口大小\n",
    "window_size = 60"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9797b76-f6a3-454a-adf6-49aa123fc3eb",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#D8BFD8'>The function takes two arguments: the dataset, which is a NumPy array you want to convert into a dataset, and the lookback, which is the number of previous time steps to use as input variables to predict the next time period—in this case, defaulted to 1.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e7a2c709-d059-463c-8cb8-514e4e01778a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 构造序列数据函数，若target为 Close，即索引为 3\n",
    "def create_dataset(dataset, lookback= 1):\n",
    "    X, y = [], []\n",
    "    for i in range(len(dataset)-lookback): \n",
    "        feature = dataset[i:(i+lookback), :]\n",
    "        target = dataset[i + lookback, 3]\n",
    "        X.append(feature)\n",
    "        y.append(target)\n",
    "    return np.array(X), np.array(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65d0b43b-cf91-4cf6-8c35-569cb41a5c8b",
   "metadata": {},
   "source": [
    " ## <font face= 'Comic Sans MS' size= 5 color= '#b8a1cf'>Feature Scaling (normalisation)</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "196a6264-411f-4a68-9744-a5feea460746",
   "metadata": {},
   "source": [
    "`MinMaxScaler()` 函数主要用于将特征数据按比例缩放到指定的范围。默认情况下，它将数据缩放到[0, 1]区间内，但也可以通过参数设置将数据缩放到其他范围。在机器学习中，`MinMaxScaler()`函数常用于不同尺度特征数据的标准化，以提高模型的泛化能力。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cf65e0ea-8f37-4db4-8ad9-bf6df686500f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 选取 AAPL[['Open', 'High', 'Low', 'Close']]作为特征, 归一化数据\n",
    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
    "scaled_data = scaler.fit_transform(AAPL[['Open', 'High', 'Low', 'Close']].values)\n",
    "\n",
    "# 获取反归一化参数(即原始数据的最小值和最大值)\n",
    "original_min = scaler.data_min_\n",
    "original_max = scaler.data_max_\n",
    "\n",
    "# scale_params是一个包含所有特征反归一化参数的列表或数组，\n",
    "# 其中第四个元素是Close价格的反归一化参数\n",
    "scale_params = original_max - original_min"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a8cb95f-3a39-445a-8e76-2d4471a6dd83",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b8a1cf'>Data set segmentation (TimeSeriesSplit)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0c7aaf92-38b9-43b7-ac17-cbf8b8a597ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(695, 60, 4) (695,)\n"
     ]
    }
   ],
   "source": [
    "# 创建数据集,数据形状为 [samples, time steps, features]\n",
    "X, y = create_dataset(scaled_data, lookback = window_size)\n",
    "print(X.shape, y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5b297b14-1d04-4a59-8cf2-27ba99a58d70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(605, 60, 4) (90, 60, 4) (605,) (90,)\n"
     ]
    }
   ],
   "source": [
    "# 使用TimeSeriesSplit划分数据集，根据需要调整n_splits\n",
    "tscv = TimeSeriesSplit(n_splits=3, test_size=90)\n",
    "# 遍历所有划分进行交叉验证\n",
    "for i, (train_index, test_index) in enumerate(tscv.split(X)):\n",
    "    X_train, X_test = X[train_index], X[test_index]\n",
    "    y_train, y_test = y[train_index], y[test_index]\n",
    "    # print(f\"Fold {i}:\")\n",
    "    # print(f\"  Train: index={train_index}\")\n",
    "    # print(f\"  Test:  index={test_index}\")\n",
    "\n",
    "# 查看最后一个 fold 数据帧的维度\n",
    "print(X_train.shape, X_test.shape, y_train.shape, y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "498e6dfd-6548-450f-9b2c-517719310b11",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b8a1cf'>Data set tensor (math.)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "74e23923-af78-463e-a37b-ac86281ce7fa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([605, 60, 4]) torch.Size([90, 60, 4]) torch.Size([605, 1]) torch.Size([90, 1])\n"
     ]
    }
   ],
   "source": [
    "# 将 NumPy数组转换为 tensor张量\n",
    "X_train_tensor = torch.from_numpy(X_train).type(torch.Tensor)\n",
    "X_test_tensor = torch.from_numpy(X_test).type(torch.Tensor)\n",
    "y_train_tensor = torch.from_numpy(y_train).type(torch.Tensor).view(-1,1)\n",
    "y_test_tensor = torch.from_numpy(y_test).type(torch.Tensor).view(-1,1)\n",
    "\n",
    "print(X_train_tensor.shape, X_test_tensor.shape, y_train_tensor.shape, y_test_tensor.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dffc4c5c-5845-4f34-bd6b-203269a203c8",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#cca3cc'>The view() function in PyTorch is used to reshape a tensor object. It’s equivalent to the reshape() function in NumPy and allows us to restructure our data to match the input shape that our BiLSTM model requires. Reshaping the data this way ensures that the BiLSTM model receives the data in the expected format. This is crucial for its ability to model the temporal dependencies in our time series data effectively.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7b7436c9-8d57-4a5f-92b0-07135b6a54c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataset = TensorDataset(X_train_tensor, y_train_tensor)\n",
    "train_loader = DataLoader(train_dataset, batch_size=32, shuffle=True)\n",
    "test_dataset = TensorDataset(X_test_tensor, y_test_tensor)\n",
    "test_loader = DataLoader(test_dataset, batch_size=32, shuffle=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80b8a5c4-5c4e-42d3-9eb4-ec4882b6a7fe",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Constructing a time series model</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1f412f8-3a0a-4655-a5b9-77862ecf0728",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#cca3cc'>双向GRU（Bidirectional Gated Recurrent Unit）网络可以通过使用nn.GRU类并设置bidirectional=True参数来完成  \n",
    "Apply a multi-layer gated recurrent unit (GRU) RNN to an input sequence. For each element in the input sequence, each layer computes the following function:\n",
    "<font face= 'Comic Sans MS' size= 3 color= '#DE3163'>$$\n",
    "\\begin{array}{ll}\n",
    "            r_t = \\sigma(W_{ir} x_t + b_{ir} + W_{hr} h_{(t-1)} + b_{hr}) \\\\\n",
    "            z_t = \\sigma(W_{iz} x_t + b_{iz} + W_{hz} h_{(t-1)} + b_{hz}) \\\\\n",
    "            n_t = \\tanh(W_{in} x_t + b_{in} + r_t \\odot (W_{hn} h_{(t-1)}+ b_{hn})) \\\\\n",
    "            h_t = (1 - z_t) \\odot n_t + z_t \\odot h_{(t-1)}\n",
    "        \\end{array}\n",
    "$$</font>\n",
    "<font face= 'Comic Sans MS' size= 3 color= '#cca3cc'>where $h_t$ is the hidden state at time $t$, $x_t$ is the input\n",
    "at time $t$, $h_{(t-1)}$ is the hidden state of the layer\n",
    "at time $t-1$ or the initial hidden state at time $0$, and $r_t$,\n",
    "$z_t$, $n_t$ are the reset, update, and new gates, respectively.\n",
    "$\\sigma$ is the sigmoid function, and $\\odot$ is the Hadamard product.</font>\n",
    "\n",
    "<font face= 'Comic Sans MS' size= 3 color= '#cca3cc'>In a multilayer GRU, the input $x^{(l)}_t$ of the $l$ -th layer\n",
    "($l \\ge 2$) is the hidden state $h^{(l-1)}_t$ of the previous layer multiplied by\n",
    "dropout $\\delta^{(l-1)}_t$ where each $\\delta^{(l-1)}_t$ is a Bernoulli random\n",
    "variable which is $0$ with probability $dropout$.</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aac70eb6-c2ab-4a6d-bb02-d4a69083bc2c",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#C2C4E2'>Model construction</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0629d7fc-2239-47e5-8adf-122ff385dbe5",
   "metadata": {},
   "outputs": [],
   "source": [
    "class BiGRU(nn.Module):\n",
    "    def __init__(self, input_size, hidden_size, num_layers, output_size):\n",
    "        # input_size 是输入特征的维度，hidden_size 是 GRU隐藏层神经单元维度（或称为隐藏状态的大小），\n",
    "        # num_layers 是 GRU网络层数，output_size 是输出维度\n",
    "        super(BiGRU, self).__init__()\n",
    "        # 通过调用 super(BiGRU, self).__init__() 初始化父类 nn.Module\n",
    "        self.hidden_size = hidden_size\n",
    "        self.num_layers = num_layers\n",
    "        self.gru = nn.GRU(input_size, hidden_size, num_layers, batch_first=True, bidirectional=True)\n",
    "        # 定义 GRU 层，使用 batch_first=True 表示输入数据的形状是 [batch_size, seq_len(time_steps), input_size]\n",
    "        # 使用 bidirectional=True 表示的是 bidirectional GRU，即双向 GRU\n",
    "        self.fc = nn.Linear(hidden_size * 2, output_size)  \n",
    "        # 定义全连接层，将 GRU的最后一个隐藏状态映射到输出维度 output_size，双向 GRU的输出维度是隐藏层维度的两倍\n",
    "\n",
    "    def forward(self, x):\n",
    "        # x: [batch_size, seq_len, input_size]\n",
    "        # h0: [num_layers * num_directions, batch_size, hidden_size]\n",
    "        # 初始化隐藏状态(hidden state)为全零张量\n",
    "        h0 = torch.zeros(self.num_layers * 2, x.size(0), self.hidden_size).to(x.device)  # 双向GRU，所以是2倍\n",
    "\n",
    "        # GRU输出, (output, hn)\n",
    "        out, _ = self.gru(x, h0)  \n",
    "        # out: tensor of shape (batch_size, seq_length(time_steps), hidden_size*2)\n",
    "\n",
    "        # 取最后一个时间步的输出（或者对输出进行平均/最大池化等操作）\n",
    "        # 这里我们选择最后一个时间步的输出\n",
    "        out = self.fc(out[:, -1, :])\n",
    "        return out"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f90adcb-e1c2-42c5-be47-d58ad93cf2db",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= '#DE3163'>*batch_first=True 表示输入数据的形状是 [batch_size, seq_len, input_size]，输出数据形状是 [batch_size, seq_len, num_directions * hidden_size]*  \n",
    "*batch_first=False 表示输入数据的形状是 [seq_len, batch_size, input_size]，输出数据形状是 [seq_len, batch_size, num_directions * hidden_size]*  \n",
    "*在时间序列模型中 seq_len 代表的就是时间步time_steps*</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "42b9037e-7fca-4071-a11e-42d06995c8fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = BiGRU(input_size = X_train.shape[2], # 输入数据的特征数量 X_train.shape[2]\n",
    "               hidden_size = 64,\n",
    "               num_layers = 1,\n",
    "               output_size = 1)\n",
    "criterion = torch.nn.MSELoss() # 定义均方误差损失函数\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.01) # 定义优化器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "67afa51e-e46a-4e6b-ab80-2c23cf7ffc40",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "==========================================================================================\n",
       "Layer (type:depth-idx)                   Output Shape              Param #\n",
       "==========================================================================================\n",
       "BiGRU                                    [32, 1]                   --\n",
       "├─GRU: 1-1                               [32, 60, 128]             26,880\n",
       "├─Linear: 1-2                            [32, 1]                   129\n",
       "==========================================================================================\n",
       "Total params: 27,009\n",
       "Trainable params: 27,009\n",
       "Non-trainable params: 0\n",
       "Total mult-adds (Units.MEGABYTES): 51.61\n",
       "==========================================================================================\n",
       "Input size (MB): 0.03\n",
       "Forward/backward pass size (MB): 1.97\n",
       "Params size (MB): 0.11\n",
       "Estimated Total Size (MB): 2.11\n",
       "=========================================================================================="
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary(model, (32, 60, 4)) # batch_size, seq_len(time_steps), input_size"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a28d9375-f3f1-48d6-b7e4-d64fafea97b7",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b8a1cf'>Model training</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd545046-54fa-4843-b246-9939df8f5163",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#C2C4E2'>模型训练与权重更新</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "886163ec-851b-4b63-8d3e-e9b15a5451c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Epoch 1/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 14.19it/s]\n",
      "Epoch 2/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 14.13it/s]\n",
      "Epoch 3/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 14.03it/s]\n",
      "Epoch 4/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 14.01it/s]\n",
      "Epoch 5/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 13.99it/s]\n",
      "Epoch 6/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 14.22it/s]\n",
      "Epoch 7/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 14.07it/s]\n",
      "Epoch 8/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 14.06it/s]\n",
      "Epoch 9/20: 100%|███████████████████████████████| 19/19 [00:01<00:00, 13.94it/s]\n",
      "Epoch 10/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.01it/s]\n",
      "Epoch 11/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.05it/s]\n",
      "Epoch 12/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 13.92it/s]\n",
      "Epoch 13/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.02it/s]\n",
      "Epoch 14/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.02it/s]\n",
      "Epoch 15/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.05it/s]\n",
      "Epoch 16/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.06it/s]\n",
      "Epoch 17/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 13.90it/s]\n",
      "Epoch 18/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.05it/s]\n",
      "Epoch 19/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.10it/s]\n",
      "Epoch 20/20: 100%|██████████████████████████████| 19/19 [00:01<00:00, 14.02it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best model saved with test loss 0.0010\n"
     ]
    }
   ],
   "source": [
    "train_losses = [] # 初始化列表来存储损失值\n",
    "test_losses = [] # 初始化列表来存储损失值\n",
    "best_loss = float('100') # 初始化为一个很大的值\n",
    "best_model = None # 初始化最佳模型为None\n",
    "\n",
    "# 训练循环\n",
    "num_epochs = 20  # 假设我们要训练 20个 epoch\n",
    "for epoch in range(num_epochs):\n",
    "    model.train()  # 初始化训练进程\n",
    "    train_loss = 0.0  # 初始化每个epoch的损失总和\n",
    "\n",
    "    pbar = tqdm(train_loader, desc=f\"Epoch {epoch+1}/{num_epochs}\",ncols=80)\n",
    "    for batch_idx, (data, target) in enumerate(pbar):\n",
    "        optimizer.zero_grad()  # 将优化器中所有参数的梯度归零\n",
    "        output = model(data)  # 每个批次的预测值\n",
    "        loss = criterion(output, target)  # 计算模型损失值(y_train_pred 与 y_train)\n",
    "        # 累加每个批次的损失\n",
    "        train_loss += loss.item() * data.size(0)\n",
    "        # 反向传播和优化\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        # 更新进度条(显示当前批次的损失)\n",
    "        pbar.update()\n",
    "\n",
    "    # 计算当前epoch的平均损失\n",
    "    average_loss = train_loss / len(train_loader.dataset)\n",
    "    train_losses.append(average_loss)\n",
    "\n",
    "    model.eval()  # 将模型设置为评估模式\n",
    "    with torch.no_grad():  # 不计算梯度以节省内存和计算资源\n",
    "        test_loss = 0.0\n",
    "        for data, target in test_loader:\n",
    "            output = model(data) # 每个批次的预测值\n",
    "            loss = criterion(output, target)\n",
    "            test_loss += loss.item() * data.size(0)\n",
    "\n",
    "        # 计算测试集的平均损失\n",
    "        test_loss = test_loss / len(test_loader.dataset)\n",
    "        test_losses.append(test_loss)\n",
    "\n",
    "    # 如果测试损失比之前的最小值小，则更新最佳模型权重\n",
    "    if test_loss < best_loss:\n",
    "        best_loss = test_loss\n",
    "        best_model = model.state_dict() \n",
    "\n",
    "# 训练循环结束后保存最佳模型\n",
    "if best_model is not None:\n",
    "    torch.save(best_model, 'model_best.pth')\n",
    "    print(f'Best model saved with test loss {best_loss:.4f}')\n",
    "else:\n",
    "    print('No model saved as no improvement was made.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b33f1d58-f71a-4923-be2d-ba552d82e1df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best epoch: 19, with test loss: 0.0010\n"
     ]
    }
   ],
   "source": [
    "best_epoch_idx = test_losses.index(min(test_losses))\n",
    "print(f\"Best epoch: {best_epoch_idx+1}, with test loss: {min(test_losses):.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d80fd1e3-06a4-4d09-a0ca-538acdb51754",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b8a1cf'>可视化训练过程（Loss损失）</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1f2004c9-af18-4ff5-8cc4-93432dae3c7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制损失图\n",
    "plt.figure(figsize=(18, 6))\n",
    "plt.plot(train_losses, label='Train Loss')\n",
    "plt.plot(test_losses, label='Test Loss')\n",
    "plt.title('Training and Test Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87869817-7061-4078-9fcd-3a3f313adc05",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#b89bd5'>Model evaluation</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97f3d8a1-2fd7-4375-8a1e-e6737ba21f6c",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b89bd5'>Evaluation indicators (MAE、RMSE、MAPE)</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51ba365a-ab72-49b0-a005-cf1c02537e26",
   "metadata": {},
   "source": [
    "<font face= 'Comic Sans MS' size= 3 color= 'red'>These metrics each evaluate different aspects of the model’s performance:\n",
    " - <font face= 'Comic Sans MS' size= 3 color= 'orange'>RMSE: This metric calculates the square root of the average squared differences between the predicted and actual values. It gives a higher penalty for large errors.\n",
    " - <font face= 'Comic Sans MS' size= 3 color= 'gold'>MAPE: This metric computes the mean of the absolute percentage difference between the actual and predicted values. It expresses the average absolute error in terms of percentage, which can be useful when you want to understand the relative prediction error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b6fc374e-40d6-4922-a644-74c93ce10b09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<All keys matched successfully>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 加载最佳模型\n",
    "model.load_state_dict(torch.load('model_best.pth'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "51552619-22af-45f7-8885-12e1ec2d3037",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Evaluating: 100%|███████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 47.55it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 0.0248\n",
      "RMSE: 0.0340\n",
      "MAPE: 3.2059%\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "def mean_absolute_percentage_error(y_true, y_pred):\n",
    "    y_true, y_pred = np.array(y_true), np.array(y_pred)\n",
    "    mask = y_true != 0\n",
    "    return np.mean(np.abs((y_true[mask] - y_pred[mask]) / y_true[mask])) * 100 if mask.any() else 0\n",
    "\n",
    "# 将模型设置为评估模式\n",
    "model.eval()\n",
    "y_pred_all = []\n",
    "y_true_all = []\n",
    "\n",
    "with torch.no_grad():\n",
    "    pbar = tqdm(test_loader, desc='Evaluating')\n",
    "    for data, target in pbar:\n",
    "        y_pred = model(data).detach().cpu().numpy()  # 确保张量在CPU上\n",
    "        y_true = target.detach().cpu().numpy()  # 确保张量在CPU上\n",
    "        y_pred_all.append(y_pred)\n",
    "        y_true_all.append(y_true)\n",
    "        pbar.update()\n",
    "\n",
    "# 合并所有批次的预测和真实值\n",
    "y_pred_all = np.concatenate(y_pred_all)\n",
    "y_true_all = np.concatenate(y_true_all)\n",
    "\n",
    "mae = np.mean(np.abs(y_pred_all - y_true_all))\n",
    "print(f\"MAE: {mae:.4f}\")\n",
    "\n",
    "rmse = np.sqrt(np.mean((y_pred_all - y_true_all) ** 2))\n",
    "print(f\"RMSE: {rmse:.4f}\")\n",
    "\n",
    "mape = mean_absolute_percentage_error(y_true_all, y_pred_all)\n",
    "print(f\"MAPE: {mape:.4f}%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9ee265f-3a4a-4ea9-8b85-7178f528224b",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b89bd5'>Inverse normalisation (.math)</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "b89bda16-a9ca-4d26-859d-e96752dcd40a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 提取Close价格的反归一化参数\n",
    "close_denorm_param = scale_params[3]  # 假设Close是第四个特征\n",
    "\n",
    "# 如果反归一化包括一个偏移量shift，需要再加上 shift_param\n",
    "# denormalized_predictions = (predictions[:, 0] * scale_param) + shift_param"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9d02b041-23fc-4c1e-84f0-5f5c31f92fad",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将训练预测 Close价格的反归一化\n",
    "y_train_pred = model(X_train_tensor).detach().numpy()\n",
    "y_train_denormalized_predictions = (y_train_pred * scale_params[3]) + original_min[3]\n",
    "\n",
    "# 将测试预测 Close价格的反归一化\n",
    "y_test_pred = model(X_test_tensor).detach().numpy()\n",
    "y_test_denormalized_predictions = (y_test_pred * scale_params[3]) + original_min[3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c997ff6-c08a-40ff-9402-d26b186d0137",
   "metadata": {},
   "source": [
    "## <font face= 'Comic Sans MS' size= 5 color= '#b89bd5'>Visualisation of results</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9686ab7-6a7b-4854-9e61-a6dda51b8c7f",
   "metadata": {},
   "source": [
    "计算训练预测与测试预测的绘图数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "fc6149eb-ae05-4da8-a9be-28e4f2e24a64",
   "metadata": {},
   "outputs": [],
   "source": [
    "# shift train predictions for plotting\n",
    "trainPredict = AAPL[window_size:X_train.shape[0]+X_train.shape[1]]\n",
    "trainPredictPlot = trainPredict.assign(TrainPrediction= y_train_denormalized_predictions)\n",
    "\n",
    "testPredict = AAPL[X_train.shape[0]+X_train.shape[1]:]\n",
    "testPredictPlot = testPredict.assign(TestPrediction= y_test_denormalized_predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2718274d-e874-4f53-a1c5-cd22502be9ba",
   "metadata": {},
   "source": [
    "绘制模型收盘价格的原始数据与预测数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "4fa553f0-d4aa-4cc3-ad3b-f8fd61d5a09b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the data\n",
    "plt.figure(figsize=(18,6))\n",
    "plt.title('BiGRU Close Price Validation')\n",
    "plt.plot(AAPL['Close'], color='blue', label='original')\n",
    "plt.plot(trainPredictPlot['TrainPrediction'], color='orange',label='Train Prediction')\n",
    "plt.plot(testPredictPlot['TestPrediction'], color='red', label='Test Prediction')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec6ae4df-d92a-4dca-a43f-228f06de57be",
   "metadata": {},
   "source": [
    "# <font face= 'Comic Sans MS' size= 6 color= '#C2C4E2'>Model prediction</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "82a44bfb-23ac-47ca-912f-10ee0d0373d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 60, 4])\n"
     ]
    }
   ],
   "source": [
    "# 假设latest_closes是一个包含最新window_size个收盘价的列表或数组\n",
    "latest_closes = AAPL[['Open', 'High', 'Low', 'Close']][-window_size:].values\n",
    "scaled_latest_closes = scaler.transform(latest_closes)\n",
    "tensor_latest_closes = torch.from_numpy(scaled_latest_closes).type(torch.Tensor).view(1, window_size, 4) \n",
    "print(tensor_latest_closes.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "95a9e3bd-fa5a-401f-b58a-b6f110db4502",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[165.61488]], dtype=float32)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用模型预测下一个时间点的收盘价\n",
    "next_close_pred = model(tensor_latest_closes).detach().numpy()\n",
    "next_close_denormalized_pred = (next_close_pred * scale_params[3]) + original_min[3]\n",
    "next_close_denormalized_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83cfc197-de00-4718-8bb8-b753440644bc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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